🔧 chore(utils.py): add setup_llm_caching function to set up LLM caching

✨ feat(main.py): call setup_llm_caching function on app startup
The `setup_llm_caching` function is added to `utils.py` to set up LLM caching. The function is then called on app startup in `main.py` using the `app.on_event("startup")` method. This improves the performance of the application by caching LLM objects.

src/backend/langflow/interface/utils.py

@@ -7,6 +7,7 @@
 import yaml
 from langchain.base_language import BaseLanguageModel
 from PIL.Image import Image
+from langflow.utils.logger import logger
 
 
 def load_file_into_dict(file_path: str) -> dict:
@@ -58,3 +59,12 @@ def try_setting_streaming_options(langchain_object, websocket):
 def extract_input_variables_from_prompt(prompt: str) -> list[str]:
  """Extract input variables from prompt."""
  return re.findall(r"{(.*?)}", prompt)
+
+
+def setup_llm_caching():
+ """Setup LLM caching."""
+ import langchain
+ from langchain.cache import SQLiteCache
+
+ logger.debug("Setting up LLM caching")
+ langchain.llm_cache = SQLiteCache()

src/backend/langflow/main.py

@@ -3,6 +3,7 @@
 
 from langflow.api import router
 from langflow.database.base import create_db_and_tables
+from langflow.interface.utils import setup_llm_caching
 
 
 def create_app():
@@ -28,6 +29,7 @@ def get_health():
 
  app.include_router(router)
  app.on_event("startup")(create_db_and_tables)
+ app.on_event("startup")(setup_llm_caching)
  return app